Transcriptome-wide analysis of microRNA–mRNA correlations in tissue identifies microRNA targeting determinants
MicroRNAs are small RNAs that regulate gene expression through complementary base pairing with their target mRNAs. A substantial understanding of microRNA target recognition and repression mechanisms has been reached using diverse empirical and bioinformatic approaches, primarily in vitro biochemica...
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| Outros autores: | , , , |
| Formato: | article |
| Idioma: | inglés |
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2023
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| Acceso en liña: | https://hdl.handle.net/20.500.12008/43094 |
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| _version_ | 1868890141760684032 |
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| author | Trinidad Barnech, Juan Manuel |
| author2 | Fort Canobra, Rafael S Trinidad Barnech, Guillermo Garat, Beatriz Duhagon, María Ana |
| author2_role | author author author author |
| author_browse | Duhagon, María Ana Fort Canobra, Rafael S Garat, Beatriz Trinidad Barnech, Guillermo Trinidad Barnech, Juan Manuel |
| author_facet | Trinidad Barnech, Juan Manuel Fort Canobra, Rafael S Trinidad Barnech, Guillermo Garat, Beatriz Duhagon, María Ana |
| author_role | author |
| collection | COLIBRI |
| dc.contributor.none.fl_str_mv | Trinidad Barnech Juan Manuel, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Biología. Fort Canobra Rafael S, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Ciencias Geológicas. Trinidad Barnech Guillermo, Universidad de la República (Uruguay). Facultad de Ingeniería. Garat Beatriz, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Biología. Duhagon María Ana, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Biología. |
| dc.creator.none.fl_str_mv | Trinidad Barnech, Juan Manuel Fort Canobra, Rafael S Trinidad Barnech, Guillermo Garat, Beatriz Duhagon, María Ana |
| dc.date.none.fl_str_mv | 2023 2024-03-14T14:53:54Z 2024-03-14T14:53:54Z |
| dc.format.none.fl_str_mv | 15 h. application/pdf |
| dc.identifier.none.fl_str_mv | Trinidad Barnech, J, Fort Canobra, R, Trinidad Barnech, G [y otros autores]. "Transcriptome-wide analysis of microRNA–mRNA correlations in tissue identifies microRNA targeting determinants". Non-Coding RNA. [en línea] 2023, 9: 15. 15 h. DOI: 10.3390/ncrna9010015. 2311-553X https://hdl.handle.net/20.500.12008/43094 10.3390/ncrna9010015 |
| dc.language.none.fl_str_mv | en eng |
| dc.publisher.none.fl_str_mv | MDPI |
| dc.relation.none.fl_str_mv | Non-Coding RNA, 2023, 9(1): 15. |
| dc.rights.none.fl_str_mv | info:eu-repo/semantics/openAccess Licencia Creative Commons Atribución (CC - By 4.0) |
| dc.source.none.fl_str_mv | reponame:COLIBRI instname:Universidad de la República instacron:Universidad de la República |
| dc.subject.none.fl_str_mv | MicroRNA 3' supplementary pairing Transcriptome TCGA Offset GC-content Correlation |
| dc.title.none.fl_str_mv | Transcriptome-wide analysis of microRNA–mRNA correlations in tissue identifies microRNA targeting determinants |
| dc.type.none.fl_str_mv | Artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| description | MicroRNAs are small RNAs that regulate gene expression through complementary base pairing with their target mRNAs. A substantial understanding of microRNA target recognition and repression mechanisms has been reached using diverse empirical and bioinformatic approaches, primarily in vitro biochemical or cell culture perturbation settings. We sought to determine if rules of microRNA target efficacy could be inferred from extensive gene expression data of human tissues. A transcriptome-wide assessment of all the microRNA–mRNA canonical interactions’ efficacy was performed using a normalized Spearman correlation (Z-score) between the abundance of the transcripts in the PRAD-TCGA dataset tissues (RNA-seq mRNAs and small RNA-seq for microRNAs, 546 samples). Using the Z-score of correlation as a surrogate marker of microRNA target efficacy, we confirmed hallmarks of microRNAs, such as repression of their targets, the hierarchy of preference for gene regions (3'UTR > CDS > 5'UTR), and seed length (6 mer < 7 mer < 8 mer), as well as the contribution of the 3'-supplementary pairing at nucleotides 13–16 of the microRNA. Interactions mediated by 6 mer + supplementary showed similar inferred repression as 7 mer sites, suggesting that the 6 mer + supplementary sites may be relevant in vivo. However, aggregated 7 mer-A1 seeds appear more repressive than 7 mer-m8 seeds, while similar when pairing possibilities at the 30 -supplementary sites. We then examined the 30-supplementary pairing using 39 microRNAs with Z-score-inferred repressive 3'-supplementary interactions. The approach was sensitive to the offset of the bridge between seed and 3'-supplementary pairing sites, and the pattern of offset-associated repression found supports previous findings. The 39 microRNAs with effective repressive 30 supplementary sites show low GC content at positions 13–16. Our study suggests that the transcriptome-wide analysis of microRNA–mRNA correlations may uncover hints of microRNA targeting determinants. Finally, we provide a bioinformatic tool to identify microRNA–mRNA candidate interactions based on the sequence complementarity of the seed and 3' -supplementary regions. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | anni_982965bfcd25de97f965abdfae070bd4 |
| identifier_str_mv | Trinidad Barnech, J, Fort Canobra, R, Trinidad Barnech, G [y otros autores]. "Transcriptome-wide analysis of microRNA–mRNA correlations in tissue identifies microRNA targeting determinants". Non-Coding RNA. [en línea] 2023, 9: 15. 15 h. DOI: 10.3390/ncrna9010015. 2311-553X 10.3390/ncrna9010015 |
| instacron_str | Universidad de la República |
| institution | Universidad de la República |
| instname_str | Universidad de la República |
| language | eng |
| language_invalid_str_mv | en |
| network_acronym_str | anni |
| network_name_str | oai-lr-anni |
| oai_identifier_str | oai:colibri.udelar.edu.uy:20.500.12008/43094 |
| publishDate | 2023 |
| publishDateSort | 2023 |
| publisher.none.fl_str_mv | MDPI |
| reponame_str | COLIBRI |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | Licencia Creative Commons Atribución (CC - By 4.0) |
| spelling | Transcriptome-wide analysis of microRNA–mRNA correlations in tissue identifies microRNA targeting determinantsTrinidad Barnech, Juan ManuelFort Canobra, Rafael STrinidad Barnech, GuillermoGarat, BeatrizDuhagon, María AnaMicroRNA3' supplementary pairingTranscriptomeTCGAOffsetGC-contentCorrelationMicroRNAs are small RNAs that regulate gene expression through complementary base pairing with their target mRNAs. A substantial understanding of microRNA target recognition and repression mechanisms has been reached using diverse empirical and bioinformatic approaches, primarily in vitro biochemical or cell culture perturbation settings. We sought to determine if rules of microRNA target efficacy could be inferred from extensive gene expression data of human tissues. A transcriptome-wide assessment of all the microRNA–mRNA canonical interactions’ efficacy was performed using a normalized Spearman correlation (Z-score) between the abundance of the transcripts in the PRAD-TCGA dataset tissues (RNA-seq mRNAs and small RNA-seq for microRNAs, 546 samples). Using the Z-score of correlation as a surrogate marker of microRNA target efficacy, we confirmed hallmarks of microRNAs, such as repression of their targets, the hierarchy of preference for gene regions (3'UTR > CDS > 5'UTR), and seed length (6 mer < 7 mer < 8 mer), as well as the contribution of the 3'-supplementary pairing at nucleotides 13–16 of the microRNA. Interactions mediated by 6 mer + supplementary showed similar inferred repression as 7 mer sites, suggesting that the 6 mer + supplementary sites may be relevant in vivo. However, aggregated 7 mer-A1 seeds appear more repressive than 7 mer-m8 seeds, while similar when pairing possibilities at the 30 -supplementary sites. We then examined the 30-supplementary pairing using 39 microRNAs with Z-score-inferred repressive 3'-supplementary interactions. The approach was sensitive to the offset of the bridge between seed and 3'-supplementary pairing sites, and the pattern of offset-associated repression found supports previous findings. The 39 microRNAs with effective repressive 30 supplementary sites show low GC content at positions 13–16. Our study suggests that the transcriptome-wide analysis of microRNA–mRNA correlations may uncover hints of microRNA targeting determinants. Finally, we provide a bioinformatic tool to identify microRNA–mRNA candidate interactions based on the sequence complementarity of the seed and 3' -supplementary regions.CSIC: I+D_2016_487CSIC: I+D_2020_566MDPITrinidad Barnech Juan Manuel, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Biología.Fort Canobra Rafael S, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Ciencias Geológicas.Trinidad Barnech Guillermo, Universidad de la República (Uruguay). Facultad de Ingeniería.Garat Beatriz, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Biología.Duhagon María Ana, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Biología.2024-03-14T14:53:54Z2024-03-14T14:53:54Z2023Artículoinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion15 h.application/pdfTrinidad Barnech, J, Fort Canobra, R, Trinidad Barnech, G [y otros autores]. "Transcriptome-wide analysis of microRNA–mRNA correlations in tissue identifies microRNA targeting determinants". Non-Coding RNA. [en línea] 2023, 9: 15. 15 h. DOI: 10.3390/ncrna9010015.2311-553Xhttps://hdl.handle.net/20.500.12008/4309410.3390/ncrna9010015reponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaenengNon-Coding RNA, 2023, 9(1): 15.Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución (CC - By 4.0)oai:colibri.udelar.edu.uy:20.500.12008/430942026-04-14T10:10:33Z |
| spellingShingle | Transcriptome-wide analysis of microRNA–mRNA correlations in tissue identifies microRNA targeting determinants Trinidad Barnech, Juan Manuel MicroRNA 3' supplementary pairing Transcriptome TCGA Offset GC-content Correlation |
| status_str | publishedVersion |
| title | Transcriptome-wide analysis of microRNA–mRNA correlations in tissue identifies microRNA targeting determinants |
| title_full | Transcriptome-wide analysis of microRNA–mRNA correlations in tissue identifies microRNA targeting determinants |
| title_fullStr | Transcriptome-wide analysis of microRNA–mRNA correlations in tissue identifies microRNA targeting determinants |
| title_full_unstemmed | Transcriptome-wide analysis of microRNA–mRNA correlations in tissue identifies microRNA targeting determinants |
| title_short | Transcriptome-wide analysis of microRNA–mRNA correlations in tissue identifies microRNA targeting determinants |
| title_sort | Transcriptome-wide analysis of microRNA–mRNA correlations in tissue identifies microRNA targeting determinants |
| topic | MicroRNA 3' supplementary pairing Transcriptome TCGA Offset GC-content Correlation |
| url | https://hdl.handle.net/20.500.12008/43094 |